Machine Learning-Based Seed Classification and Controlled Sowing System
As an Agricultural country, Pakistan has witnessed growth in various factors, including the agriculture industry. The proposed system aims to classify seeds before sowing them. The process of seed quality control involves segregating defective seeds from healthy seeds using image processing and machine learning techniques. Traditionally, seeds are classified based on their color and shape. However, the proposed system aims to utilize advanced technologies to ensure precise classification and better quality control. To automate the process of seed classification, a robot-like system will be designed to perform mechanical and electrical work. The system will use machine learning algorithms to classify seeds based on their size, color and shape. This approach will ensure that only high-quality seeds are used for sowing, thereby increasing the chances of a better yield.
Keywords: Machine Learning, Control Systems, Seed Classification
Tools: Raspberry Pi-4, Raspbian, OpenCV, Image Processing, Convolutional Neural Networks
Department: Department of Electrical Engineering
Project Team Members
| Name |
Email |
|
Muhammad Behzad Hassan
|
behzad2019@namal.edu.pk |
|
Ahmad Hassan
|
hassan2019@namal.edu.pk |
|
Muhammad Zaheer Akram
|
zaheer2019@namal.edu.pk |
Project Poster
